Geometric potential of cartosat-1 stereo imagery

Cartosat-1 satellite, launched by Department of Space (DOS), Government of India, is dedicated to stereo viewing for large scale mapping and terrain modelling applications. This stereo capability fills the limited capacity of very high resolution satellites for three-dimensional point determination and enables the generation of detailed digital elevation models (DEMs) not having gaps in mountainous regions like for example the SRTM height model.The Cartosat-1 sensor offers a resolution of 2.5m GSD in panchromatic mode. One CCD-line sensor camera is looking with a nadir angle of 26' in forward direction, the other 5' aft along the track. The Institute "Area di Geodesia e Geomatica"-Sapienza Università di Roma and the Institute of Photogrammetry and Geoinformation, Leibniz University Hannover participated at the ISPRS-ISRO Cartosat-1 Scientific Assessment Programme (CSAP), in order to investigate the generation of Digital Surface Models (DSMs) from Cartosat-1 stereo scenes. The aim of this work concerns the orientation of Cartosat-1 stereo pairs, using the given RPCs improved by control points and the definition of an innovative model based on geometric reconstruction, that is used also for the RPC extraction utilizing a terrain independent approach. These models are implemented in the scientific software (SISAR-Software per Immagini Satellitari ad Alta Risoluzione) developed at Sapienza Università di Roma. In this paper the SISAR model is applied to different stereo pairs (Castelgandolfo and Rome) and to point out the effectiveness of the new model, SISAR results are compared with the corresponding ones obtained by the software OrthoEngine 10.0 (PCI Geomatica).By the University of Hannover a similar general satellite orientation program has been developed and the good results, achieved by bias corrected sensor oriented RPCs, for the test fields Mausanne (France) and Warsaw (Poland) have been described.For some images, digital height models have been generated by automatic image matching with least squares method, analysed in relation to given reference height models. For the comparison with the reference DEMs the horizontal fit of the height models to each other has been checked by adjustment

Performance of Angle of Arrival Detection Using MUSIC Algorithm in Inter-Satellite Link

An attitude of satellite is not always static, sometimes it moves randomly and the antenna pointing of satellite is harder to achieve line of sight communication to other satellite when it is outage by tumbling effect. In order to determine an appropriate direction of satellite antenna in inter-satellite link, this paper analyze estimation performance of the direction of arrival (DoA) using MUSIC algorithm from connected satellite signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system (GPS) attitude determination. The proposed method is characterized by taking signal source from connected satellites, after that the main satellite processed the information to obtain connected satellites antenna direction. The simulation runs only on the direction of azimuth. The simulation result shows that MUSIC algorithm processing time is faster than satellite movement time in orbit on altitude of 830 km with the period of 101 minutes. With the use of a 50 elements array antenna in spacing of 0.5 wavelength, the total of 20 angle of arrival (AoA) can be detected in 0.98 seconds of processing time when using MUSIC algorithm

On-Orbit Results from an Ultra-Low SWaP Black Silicon Star Tracker

In August 2019, two 1.5U AeroCube-10 satellites built by The Aerospace Corporation were deployed from a Cygnus resupply spacecraft. Each of the satellites has two star trackers which are many times smaller than commercially available alternatives. The significant size reduction is enabled by the SiOnyx XQE-0920 sensor which offers dramatically improved visible and near-infrared sensitivity in an uncooled CMOS platform. This allows the use of a smaller-aperture lens than traditionally used in small form factor star trackers, while maintaining the ability to detect stars of magnitude 5. The reduced volume enables innovative system engineering trades such as forgoing star tracker baffles, and instead flying multiple sensors on the same spacecraft to combat stray light by using the spacecraft body itself as a shield. The additional interior volume made available also enables more capable missions in smaller CubeSat form factors. On-orbit results are presented showing angular accuracy and solution availability statistics as a function of angular rotation rate. A calibration technique to compensate for optical distortion is also presented, which enables the use of a low-cost COTS lens with a wide field of view. Despite the extremely small volume, the star tracking performance is comparable to units many times larger

The GLAS Algorithm Theoretical Basis Document for Precision Attitude Determination (PAD)

The Geoscience Laser Altimeter System (GLAS) was the sole instrument for NASAs Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry mission. The primary purpose of the ICESat mission was to make ice sheet elevation measurements of the polar regions. Additional goals were to measure the global distribution of clouds and aerosols and to map sea ice, land topography and vegetation. ICESat was the benchmark Earth Observing System (EOS) mission to be used to determine the mass balance of the ice sheets, as well as for providing cloud property information, especially for stratospheric clouds common over polar areas

Reconstructing Spectral Scenes using Statistical Estimation to Enhance Space Situational Awareness

A new sensor, the Advanced Electro-Optical System (AEOS) Spectral Imaging Sensor (ASIS) has been developed at the Maui Space Surveillance Complex (MSSC). ASIS is capable of collecting resolved imagery of space objects in 10\u27s-100\u27s of spectral bands while using an adaptive optics system. However, the stringent requirements of collecting ground-based images requires a sensor that induces spectral blurring. Post-processing algorithms to remove this blurring are required to fully exploit these spectral images. This research focuses on developing the reconstruction algorithms, based on proven estimation theories, required to spectrally deblur the images collected from ASIS. Additionally, the research will expand the algorithm to also estimate the linear polarizations of the scene. The Cramer-Rao lower bounds on two key performance parameters, the spectral resolution and accuracy, of the reconstruction algorithm will also be calculated. Through the examination of these lower bounds a performance metric can be determined. This metric can be used to compare the ability of the algorithm to work on different spectral sensors

The Juno Magnetic Field Investigation

The Juno Magnetic Field investigation (MAG) characterizes Jupiter's planetary magnetic field and magnetosphere, providing the first globally distributed and proximate measurements of the magnetic field of Jupiter. The magnetic field instrumentation consists of two independent magnetometer sensor suites, each consisting of a tri-axial Fluxgate Magnetometer (FGM) sensor and a pair of co-located imaging sensors mounted on an ultra-stable optical bench. The imaging system sensors are part of a subsystem that provides accurate attitude information (to approx. 20 arcsec on a spinning spacecraft) near the point of measurement of the magnetic field. The two sensor suites are accommodated at 10 and 12 m from the body of the spacecraft on a 4 m long magnetometer boom affixed to the outer end of one of 's three solar array assemblies. The magnetometer sensors are controlled by independent and functionally identical electronics boards within the magnetometer electronics package mounted inside Juno's massive radiation shielded vault. The imaging sensors are controlled by a fully hardware redundant electronics package also mounted within the radiation vault. Each magnetometer sensor measures the vector magnetic field with 100 ppm absolute vector accuracy over a wide dynamic range (to 16 Gauss = 1.6 x 10(exp. 6) nT per axis) with a resolution of approx. 0.05 nT in the most sensitive dynamic range (+/-1600 nT per axis). Both magnetometers sample the magnetic field simultaneously at an intrinsic sample rate of 64 vector samples per second. The magnetic field instrumentation may be reconfigured in flight to meet unanticipated needs and is fully hardware redundant. The attitude determination system compares images with an on-board star catalog to provide attitude solutions (quaternions) at a rate of up to 4 solutions per second, and may be configured to acquire images of selected targets for science and engineering analysis. The system tracks and catalogs objects that pass through the imager field of view and also provides a continuous record of radiation exposure. A spacecraft magnetic control program was implemented to provide a magnetically clean environment for the magnetic sensors, and residual spacecraft fields andor sensor offsets are monitored in flight taking advantage of Juno's spin (nominally 2 rpm) to separate environmental fields from those that rotate with the spacecraft

Gaia in-orbit realignment. Overview and data analysis

The ESA Gaia spacecraft has two Shack-Hartmann wavefront sensors (WFS) on its focal plane. They are required to refocus the telescope in-orbit due to launch settings and gravity release. They require bright stars to provide good signal to noise patterns. The centroiding precision achievable poses a limit on the minimum stellar brightness required and, ultimately, on the observing time required to reconstruct the wavefront. Maximum likelihood algorithms have been developed at the Gaia SOC. They provide optimum performance according to the Cr\'amer-Rao lower bound. Detailed wavefront reconstruction procedures, dealing with partial telescope pupil sampling and partial microlens illumination have also been developed. In this work, a brief overview of the WFS and an in depth description of the centroiding and wavefront reconstruction algorithms is provided.Comment: 14 pages, 6 figures, 2 tables, proceedings of SPIE Astronomical Telescopes + Instrumentation 2012 Conference 8442 (1-6 July 2012

Development of a low-cost multi-camera star tracker for small satellites

This thesis presents a novel small satellite star tracker that uses an array of low-cost, off the shelf imaging sensors to achieve high accuracy attitude determination performance. The theoretical analysis of improvements in star detectability achieved by stacking images from multiple cameras is presented. An image processing algorithm is developed to combine images from multiple cameras with arbitrary focal lengths, principal point offsets, distortions, and misalignments. The star tracker also implements other algorithms including the region growing algorithm, the intensity weighted centroid algorithm, the geometric voting algorithm for star identification, and the singular value decomposition algorithm for attitude determination. A star tracker software simulator is used to test the algorithms by generating star images with sensor noises, lens defocusing, and lens distortion. A hardware prototype is being assembled for eventual night sky testing to verify simulated performance levels. Star tracker flight hardware is being developed in the Laboratory for Advanced Space Systems at Illinois (LASSI) at the University of Illinois at Urbana Champaign for future CubeSat missions

A Monocular SLAM Method to Estimate Relative Pose During Satellite Proximity Operations

Automated satellite proximity operations is an increasingly relevant area of mission operations for the US Air Force with potential to significantly enhance space situational awareness (SSA). Simultaneous localization and mapping (SLAM) is a computer vision method of constructing and updating a 3D map while keeping track of the location and orientation of the imaging agent inside the map. The main objective of this research effort is to design a monocular SLAM method customized for the space environment. The method developed in this research will be implemented in an indoor proximity operations simulation laboratory. A run-time analysis is performed, showing near real-time operation. The method is verified by comparing SLAM results to truth vertical rotation data from a CubeSat air bearing testbed. This work enables control and testing of simulated proximity operations hardware in a laboratory environment. Additionally, this research lays the foundation for autonomous satellite proximity operations with unknown targets and minimal additional size, weight, and power requirements, creating opportunities for numerous mission concepts not previously available